Evaluation of different suspicion indices in identifying patients with Niemann-Pick disease Type C in clinical practice: a post hoc analysis of a retrospective chart review

Challenges in the Definitive Diagnosis of Niemann-Pick Type C-Leaky Variants and Alternative Transcripts

Niemann-Pick type C (NPC, ORPHA: 646) is a neuro-visceral, psychiatric disease caused predominantly by pathogenic variants in the NPC1 gene or seldom in NPC2. The rarity of the disease, and its wide range of clinical phenotypes and ages of onset, turn the diagnosis into a significant challenge. Other than the detailed clinical history, the typical diagnostic work-up for NPC includes the quantification of pathognomonic metabolites. However, the molecular basis diagnosis is still of utmost importance to fully characterize the disorder. Here, the authors provide an overview of splicing variants in the NPC1 and NPC2 genes and propose a new workflow for NPC diagnosis. Splicing variants cover a significant part of the disease-causing variants in NPC. The authors used cDNA analysis to study the impact of such variants, including the collection of data to classify them as leaky or non-leaky pathogenic variants. However, the presence of naturally occurring spliced transcripts can misdiagnose or mask a pathogenic variant and make the analysis even more difficult. Analysis of the NPC1 cDNA in NPC patients in parallel with controls is vital to assess and detect alternatively spliced forms. Moreover, nonsense-mediated mRNA decay (NMD) analysis plays an essential role in evaluating the naturally occurring transcripts during cDNA analysis and distinguishing them from other pathogenic variants' associated transcripts.

The Antifungal Antibiotic Filipin as a Diagnostic Tool of Cholesterol Alterations in Lysosomal Storage Diseases and Neurodegenerative Disorders

Cholesterol is the most considerable member of a family of polycyclic compounds understood as sterols, and represents an amphipathic molecule, such as phospholipids, with the polar hydroxyl group located in position 3 and the rest of the molecule is completely hydrophobic. In cells, it is usually present as free, unesterified cholesterol, or as esterified cholesterol, in which the hydroxyl group binds to a carboxylic acid and thus generates an apolar molecule. Filipin is a naturally fluorescent antibiotic that exerts a primary antifungal effect with low antibacterial activity, interfering with the sterol stabilization of the phospholipid layers and favoring membrane leakage. This polyene macrolide antibiotic does not bind to esterified sterols, but only to non-esterified cholesterol, and it is commonly used as a marker to label and quantify free cholesterol in cells and tissues. Several lines of evidence have indicated that filipin staining could be a good diagnostic tool for the cholesterol alterations present in neurodegenerative (e.g., Alzheimer's Disease and Huntington Disease) and lysosomal storage diseases (e.g., Niemann Pick type C Disease and GM1 gangliosidosis). Here, we have discussed the uses and applications of this fluorescent molecule in lipid storage diseases and neurodegenerative disorders, exploring not only the diagnostic strength of filipin staining, but also its limitations, which over the years have led to the development of new diagnostic tools to combine with filipin approach.

Hepatic Manifestations of Mendelian Disorders of Cholesterol Biosynthesis and Cellular Metabolism

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Favorable outcomes following early onset oral miglustat in early infantile Niemann Pick Type C

Niemann-Pick disease Type C (NPC) is a rare autosomal recessive neurovisceral lysosomal disorder. Perinatal and early infantile onset NPC are the most severe types of the disease. Early infantile type is characterized by a rapidly progressive neurodegenerative course, which entails significant morbidity and usually results in death within 5 years. Miglustat, an iminosugar that selectively inhibits the glycosylceramide synthase enzyme, is known to stabilize or delay neurological progression in individuals with NPC, but its impact on affected infants is yet to be elucidated. We present two siblings with early infantile NPC due to the previously reported devastating homozygous mutation c.2279_2281delTCT in NPC1. Their considerably discrepant neurological disease courses were dependent on the timing of initiation of miglustat treatment. The outcomes support the significant role of early treatment with miglustat in the disease course of early infantile NPC and suggest that therapy should be considered even before the occurrence of neurological involvement. Moreover, this report emphasizes the importance of early diagnosis, in light of the availability of a potential disease-modifying medication.

Recessive Ataxia Differential Diagnosis Algorithm (RADIAL) Versus Specific Niemann-Pick Type C Suspicion Indices: A Retrospective Algorithm Comparison

Early diagnosis of Niemann-Pick disease type C (NPC) is crucial to slow the progression of neurological manifestations. Different tools were developed to aid diagnosis of NPC, but to date, no study has compared their performance. We aimed to compare the RADIAL algorithm, intended for the differential diagnosis of autosomal recessive cerebellar ataxias (ARCAs) and NPC-specific suspicion indices (SIs). This study was a retrospective analysis of data from 834 patients with molecularly confirmed ARCAs, including 57 NPC cases (RADIAL cohort). We aimed to compare the algorithm performance of RADIAL (Top 1 and Top 3) with that of four SIs (Original, Refined, 2/3 and 2/7) in discriminating NPC cases and non-NPC cases. We also identified ARCAs closely related to NPC as those with low specificity to detect non-NPC cases and described differential and overlapping features with NPC. Overall, excellent sensitivity and specificity (> 0.90) were achieved with both RADIAL and SI tools for NPC cases. The highest sensitivity was attained with the 2/7 SI, Refined SI and Top 3 RADIAL algorithms. Top 1 and Top 3 RADIAL were the most specific tools, followed by the Original SI. The individual comparison of each ARCA revealed that Wilson disease, PLA2G6-associated neurodegeneration, and hypomyelinating leukodystrophy (POLR3A) are frequent NPC false positives (PLA2G6 and POL3A only with the SIs). Both RADIAL and SI diagnostic approaches showed strong discriminatory potential and may be useful screening tools in different clinical contexts.